US8201122B2  Computing resistance sensitivities with respect to geometric parameters of conductors with arbitrary shapes  Google Patents
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Abstract
Description
Manufacturing variability affects integrated circuit resistance values at various points on the integrated circuit. For example, lithography, etching, and chemicalmechanical polishing, whether systematic or random, may combine to impact the boundaries of “shapes” printed on a wafer, thus leading to variations in their electrical properties. These shapes may correspond to pads, a device (e.g., transistor), wires, and/or vias that connect conductors between two metal layers or between a device layer and a metal layer.
A computer system selects a shape included in an integrated circuit's layout file, and then selects a first contact and a second contact located on the shape. Next, the computer system computes a nominal resistance between the first contact and the second contact based upon a nominal boundary of the shape, and then computes an adjoint system vector based upon a perturbed boundary of the shape. Using the adjoint system vector, the computer system computes a resistance sensitivity between the first contact and the second contact. In turn, the computer system simulates the integrated circuit using the computed nominal resistance and the computed resistance sensitivity.
The foregoing is a summary and thus contains, by necessity, simplifications, generalizations, and omissions of detail; consequently, those skilled in the art will appreciate that the summary is illustrative only and is not intended to be in any way limiting. Other aspects, inventive features, and advantages of the present disclosure, as defined solely by the claims, will become apparent in the nonlimiting detailed description set forth below.
The present disclosure may be better understood, and its numerous objects, features, and advantages made apparent to those skilled in the art by referencing the accompanying drawings, wherein:
Certain specific details are set forth in the following description and figures to provide a thorough understanding of various embodiments of the disclosure. Certain wellknown details often associated with computing and software technology are not set forth in the following disclosure, however, to avoid unnecessarily obscuring the various embodiments of the disclosure. Further, those of ordinary skill in the relevant art will understand that they can practice other embodiments of the disclosure without one or more of the details described below. Finally, while various methods are described with reference to steps and sequences in the following disclosure, the description as such is for providing a clear implementation of embodiments of the disclosure, and the steps and sequences of steps should not be taken as required to practice this disclosure. Instead, the following is intended to provide a detailed description of an example of the disclosure and should not be taken to be limiting of the disclosure itself. Rather, any number of variations may fall within the scope of the disclosure, which is defined by the claims that follow the description.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or computer program product. Accordingly, aspects of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.
Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a nonexhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a readonly memory (ROM), an erasable programmable readonly memory (EPROM or Flash memory), an optical fiber, a portable compact disc readonly memory (CDROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electromagnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a standalone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
Aspects of the present disclosure are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The following detailed description will generally follow the summary of the disclosure, as set forth above, further explaining and expanding the definitions of the various aspects and embodiments of the disclosure as necessary.
Manufacturing effects may cause nominal boundary 110 to “distort” during manufacturing. The example shown in
In order to effectively simulate an integrated circuit, this disclosure computes resistance variations of an integrated circuit's “shapes” caused by manufacturing effects. This disclosure computes resistance variations using resistance sensitivities with respect to shape perturbations due to manufacturing effects. In turn, the resistance sensitivities are utilized during simulation to effectively simulate the integrated circuit (see
Next, processing retrieves manufacturing process variations from process variations store 335 and generates a perturbed layout file based upon the nominal layout file and the process variations. For example, the nominal layout file may include straight lines and sharp angles, while the perturbed layout file may include arbitrary shapes (see
Next, processing computes resistance sensitivities for the arbitrary shapes included in the perturbed layout file using a finite element method and an adjoint method (predefined process block 340, see
At step 410, processing selects a shape and identifies contacts on the shape. Processing then assembles a system matrix (M) input vector (B), and output vector (C^{T}) for finite element method (FEM) computations. As those skilled in the art can appreciate, the system matrix is a table with a matrix of coefficients for m_{ij }points where i and j are the global indices of the nodes of triangles (see
Mv=B; (System Formula) (1)
Iq=C ^{T} v; (Total Current through port q) (2)
R=1/Iq (Resistance) (3)
Since sensitivity is of interest, processing uses an explicit system formula of (1) above, resulting in
M(P)v(P)=B(P) (4)
where “P” is a vector of geometrical parameters, such as the dimensions of a shape and the relative position of the contacts within the shape. As such, the impact of the variation of such parameters “P” on the computed resistances may be effectively evaluated. Using the explicit system formula (4) above, processing uses the assembled system matrix M and input vector B to compute v(P).
Processing then uses formula (2) above and computes I_{q }using C^{T }and the computed v. Finally, processing uses formula (3) above to compute the nominal resistance R based upon the computed I_{q }(refer to the Resistance Calculation section below,
At step 420, processing computes the derivative of the system matrix M relative to the vector P (system matrix derivative, refer to the Derivative Computation section below,
Next, at step 435, processing computes a derivative of the input vector B (input vector derivative), which was assembled back in step 410. Processing then computes a derivative of the output vector C (output vector derivative, step 440), which was also assembled back in step 410 (refer to the Derivative Computation section below,
At step 445, processing uses the system matrix (M) and output vector (C) assembled above to solve for the adjoint system vector (A) using the adjoint system formula:
MΛ=C=>Λ=CM ^{−1} (5)
Using formula (2) above, the derivative of output current I_{q }with respect to P (output current derivative) is:
dI _{q} /dP=(dC ^{T} /dP)v+C ^{T}(dv/dP) (6)
Using formula (1) above, dv/dP may be solved as:
dv/dp=M ^{−1} {dB/dP−(dM/dP)v} (7)
Plugging formula (7) into formula (6) yields:
dI _{q} /dP=(dC ^{T} /dP)v+C ^{T} M ^{−1} {dB/dP−(dM/dP)v} (8)
And, substituting C^{T}M^{−1 }in formula (8) with formula (5) yields:
dI _{q} /dP=(dC ^{T} /dP)v+Λ{dB/dP−(dM/dP)v} (9)
Using formula (9), processing computes the derivative of the output current dI_{q}/dP at step 450.
As discussed in step 415, R=1/I_{q}. As such, the derivative of R=1/I_{q }with respect to P yields:
dR _{pq} /dP=−R ^{2} _{pq}(dI _{q} /dP) (10)
Processing uses formula 10 at step 455 to compute the resistance sensitivity dR_{pq}/dP and store the resistance sensitivity in resistance store 145. A determination is made as to whether there are more contacts to select on the selected shape (decision 460). For example, referring back to
A determination is made as to whether there are more shapes to select in the layout (decision 470). If there are more shapes to select, decision 470 branches to “Yes” branch 472, which loops back to select and process the next shape. This looping continues until each shape is processed, at which point decision 470 branches to “No” branch 478 whereupon processing returns at 480.
A further detail description is below regarding resistance calculations, finite element method computations, adjoint sensitivity analysis, output function definition, and computing derivatives with respect to the geometrical parameter vector P. Some symbols in the description below may not be the same as those used in the above description. For example, the description above uses the symbol “v” for potential and the description below uses the symbol “φ” for potential. Those skilled in the art can appreciate and correlate the symbols used in the description below with the symbols used in the description above.
In a variationaware VLSI extraction flow, both the nominal resistance and the sensitivity of the resistance to the geometrical variations may be utilized to predict the resistance of a slightly perturbed shape. More precisely, one may approximate the resistance function using a multivariate, firstorder Taylor expansion
where Δp_{m }is the perturbation around a nominal value of a parameter “p_{m},” and δR/δp_{m }is the sensitivity (expressed as a partial derivative) of the resistance with respect to such perturbation. An algorithm for computing such sensitivities for conductors of arbitrary shapes is presented in this disclosure. In particular, a FEM resistance calculation tool may be augmented with a sensitivity calculation capability using adjoint variational analysis.
In a VLSI layout extraction flow, FEM may be used in two different approaches. The first approach is to compute accurate lookup tables of specific wiring patterns for which the wirelike resistance formula will fail. Such computations are done offline and do not impact the processing cost of the resistance extraction step. The second approach is online where FEM is applied very selectively. In the latter approach, caching and pattern recognition are extensively employed to reduce the number of times the FEM solver is actually called. Another important aspect is that in the full layout extraction flow, the overall performance is gated by the capacitance extraction phase rather than the resistance extraction phase. This disclosure discusses FEMbased resistance sensitivities within the overall VLSI layout extraction context.
Resistance Calculation
Resistance calculation is governed by the following partial differential equations:
∇·(σ(r)(−∇φ(r)))=0 rεD
σ(r)(−∇φ(r))·{circumflex over (n)}=0 rε∂D _{nc }
φ(r)=φ_{0 } rε∂D _{c} (12)
where φ(r) is the electric potential, σ(r) is the electric conductivity of the material, D is the closed domain of the problem, δD_{nc }is the union of the boundary segments which are not assigned a particular potential (referred to as nonterminal), δD_{c }is the union of the boundary segments which are assigned a specific potential (referred to as terminal), and {circumflex over (n)} is the normal to the boundary surface. The second equation is the Neumann boundary condition at the nonterminal boundary of the problem and indicates that the current does not flow outside of the metal (the perpendicular current component vanishes). The last equation is the Dirichlet boundary condition at the terminals with prescribed potential φ_{0}. For a set of N_{c }contacts the resistance between contacts p and q is computed by assigning unit potential to contact p (e.g., φp=V_{p }(=1), and assigning zero potential to all other contacts. In turn, formula 12 above may be solved to find φ(r) everywhere in D and subsequently computes the total current entering contact q as
where δD_{cq }is the boundary of contact q. In turn, the required resistance is R(p,q)=V_{p}/I_{q}. As can be seen, one simulation is required to compute an entire row of the resistance matrix R(p,x): 1≦x≦N_{c}.
Finite Element Method (FEM)
For the sake of simplicity, FEM is discussed below in a twodimensional (2D) aspect. As those skilled in the art can appreciate, FEM as discussed below may also be extended to a threedimensional aspect. Since formula (12) above has mixed DirichletNeumann boundary conditions, the continuous FEM formulation is derived from minimizing the following energy functional:
E(φ(x,y))=∫_{D}σ(x,y)∇φ(x,y)·∇φ(x,y)dxdy (13)
Referring to FIG. 8A's diagram 800, which includes contacts 805 and 810, in order to solve for φ(r), the geometry is first subdivided into smaller elements. For 2D structures, the Delaunay triangulation is used for the discretization, since it tends to guarantee triangles of reasonable aspect ratios. The resulting elements are described by the coordinates of their nodes. Each node has a unique global index to identify it in the mesh as well as a local index within each triangle it belongs to. Clearly, a given node may have more than one local index, since it may belong to more than one triangle. The local nodes shown in triangle T_{k } 815 are labeled k_{1 } 820, k_{2 } 825, and k_{3 } 830. The potential within each triangular element is then approximated using a basis of polynomial functions. For simplicity, this basis is taken to be that of firstorder polynomials, so that
φ(x,y)=β_{x} x+β _{y} y+β _{0} (14)
Consequently, the potential of every element T_{k } 815 is described by the three unknown potentials of its nodes φ(k_{1}), φ(k_{2}), and φ(k_{3}) and three coefficients β_{x}, β_{y}, and β_{0 }of formula (14). The gradient of the potential in formula (14) may then be rewritten in terms of the nodal potential as
where the coordinates of the node k_{i }are (x_{ki}, y_{ki}); α_{Tk }is the area of triangle 815, and {circumflex over (x)} and ŷ are the unit vectors of the x and y axis. Substituting in formula (13) the discretized quadratic form
E(φ)=φ_{n} ^{T} Aφ _{n} (15)
where φ_{n }is the vector of all node potentials in the mesh and A is the system matrix. The elements of A are written in a compact form
where i and j are the global indices of the nodes, k is the index of the triangle, (i,j)εT_{k }means that i and j belong to a triangle T_{k}, and Σ(k) is the conductivity of the region bounded by triangle T_{k}. It is further assumed that the local indices of i and j in T_{k }are k_{i }and k_{j}, respectively. Formula (15) is then rewritten as
where φ_{1 }is the vector of the unknown potential (potential of all N noncontact nodes), φ_{2 }is the vector of the known fixed potential (potential of N_{f }nodes on the contacts), A_{11 }represents the self interaction of the noncontact nodes, A_{12}=A^{T} _{21 }mutual interaction of contact and noncontact nodes, and A_{22 }self interactions of the contact nodes. Formula (17) is then minimized with respect to the unknown potential vector φ_{1 }to obtain
A _{11}φ_{1} =−A _{12}φ_{2} (18)
Formula (18) is cast in the standard compact form Mφ=b, where M=A_{11}, φ=φ_{1 }and b=−A_{12}φ_{2}. This linear system is then solved for φ to obtain the potential everywhere inside the domain D. As discussed above, in order to obtain a sensitivity calculation, the dependence of M, φ, and b on the problem parameters is made explicit, so the above linear system is written as
M(P)φ(P)=b(P) (19)
where P is a vector of geometrical parameters, such as the dimensions of the structure and the relative position of the contacts within it. The goal is to efficiently evaluate the impact of the variation of such parameters on the computed resistances.
Adjoint Sensitivity Analysis
The adjoint sensitivity computation is an efficient algorithm for finding the sensitivity of a given vector f(P, φ(P)) of length n_{0 }with respect to a parameter vector P of length n_{P}. A simple derivation of the adjoint method is summarized below.
Taking the total derivative of f(P, φ(P)) with respect to P results in
where
are matrices of size n_{o}×n_{p},
is a
matrix of size n_{o}×N and
is a matrix of size N×n_{p}.
Direct sensitivity methods are based on computing
using a finite difference (FD) perturbation for each component of P, which is computationally very expensive since it requires n_{p }independent system solves. However, taking the derivative of linear system (19) with respect to P results in the formula
Solving for
and substituting into (20) results in the formula
Defining now the adjoint vector Λ as the solution of the adjoint linear system
the following equation is derived for the adjoint sensitivity method
The main advantage of the adjoint method is that with only two system solves, one for the nominal system (19) and one for the adjoint system (23), the sensitivity of ƒ(P,φ(P)) with respect to an arbitrary number of parameters n_{P }may be computed. In other words, when compared with the standard direct sensitivity method, the time complexity of the adjoint method is independent of the number of parameters. Furthermore, its accuracy is independent of numerical differentiation.
Defining the Output Function
Recall that the resistance
is a function of the total current I_{q }at a particular contact q, which in turn is a linear function of the potential φ(r). The total derivative of the resistance with respect to the parameter vector P is given by the formula
Consequently, the quantity of interest to extract R_{pq }is the total current at contact q due to a unit potential V_{p}=1 excitation at contact p, (e.g., the qth component of the output vector is given by f(P,φ(P))(q)=I_{q}). Referring to
where bounding surface δB_{q } 840 is constructed as the union of the sides of the triangles touching contact q 835 at a single point (marked with “X's”). Without loss of generality, the local numbering of these triangles is made such that the point touching the contact may be numbered I_{1}, where I is the index of the triangle. Let the side of triangle T_{i }belonging to bounding surface δB_{q } 840 be referred to as δB_{ql } 840. Note that the local normal to the boundary is the unit vector in direction of A(l_{1}), i.e., {circumflex over (n)}={circumflex over (n)}(l_{1})=Â(l_{1}). The I_{q }integral is discredited as
where the relation
is used.
Note that due to the assumed local indexing of triangle T_{l}, node l_{1 }is on the boundary of the contact and φ(l_{1})=0. This leads to the formula
which is simply the addition of the contributions of all the points on boundary surface δB_{q } 840 that are connected to points on the contact boundary. A careful investigation of this formula reveals that with the aid of formula (17), it can be cast in the following compact form
I _{q} =S _{q}(A _{21}φ_{1} =A _{22}φ_{2}) (26)
where S_{q }is a row vector of zeros and ones and the rest of the notation is as in (17). S_{q }has ones at columns corresponding to the global indices of the nodes representing contact q 835. Formula (26) indicates that the total current depends linearly on the potential of any point connected to a boundary point through a common triangle. More importantly, formula (26) indicates that the entries of the output matrices S_{q}A_{21 }and S_{q}A_{22}, along with those of both the system matrix M and the RHS vector b all share the same formulas, i.e., they all rely on elements of the form in formula (26). This is useful when derivatives of such elements with respect to geometrical variations are computed (discussed below). Finally, formula (26) may be cast in a more compact linear relation between the current and potential
I(φ(P),P)=C _{1} ^{T}(P)φ(P)+C _{2} ^{T}(P)φ_{2} (27)
where φ(P) is the unknown potential of the noncontact nodes, and φ_{2 }is the vector of fixed potentials of the contact nodes and is of length N_{f}, while C_{1}(P) and C_{2}(P) are known parameterdependent matrices of size N×n_{0 }and N_{f}×n_{o}, respectively. Note that the above derivation is valid only for contacts that are assigned zero potential, i.e., q≠p, where p is the index of the excited contact. However this is not a limitation since only one contact is assigned a nonzero potential and the selfresistance of such contact is given by the sum of all the mutual resistances of the contact
Finally, the derivatives of the current function required for the adjoint formulas (23) and (24) are given by
where p_{m }is the mth component of P.
Derivative Computations with Respect to Parameter Vector P
In this subsection, the derivatives of the different matrix and vector entries with respect to the parameter vector P are computed. First, the matrix elements of the system matrix M, the right hand side vector b and the output matrices C_{1 }and C_{2 }are all computed from formula (26) and therefore computing the derivative of formula (26) with respect to the geometrical parameters covers all the required derivatives. Second, since all the entries of the matrices and vectors depend solely on the coordinates of the nodes, all geometrical perturbations may be defined by their effect on such nodal coordinates. Using formula (26) the derivative of any matrix element with respect to the geometrical parameter p_{m }is given by
where z_{l }is one of the six coordinates (x and y coordinates of the three nodes of the triangle) on which the term A(i,j) depends. The global indices of the nodes of triangle T_{k }are (i,j,l) and the corresponding local indices are (k_{i}, k_{j}, k_{l}). The computation of
is illustrated by the following example. The goal is to compute
where z_{l}=x_{l}, the x coordinate of the lth global node in triangle T_{k}. This is achieved through the following algebra steps
Next, the chain rule factor
in formula (18) may be computed using an instance of a generic perturbation that implements uniform shape changes such as expansion or shrinking, as shown in
Since this type of perturbations affects only the boundary of the structure, all the internal nodes will remain unchanged, i.e.,
for any z_{l }coordinate of an internal node. Only nodes defining the outer boundary will change. The direction of the boundary node perturbation is in the average direction of the normals to both boundary segments connected through the node. This is direction {circumflex over (n)} in
where ∥v∥ is the length of vector v and
Consequently, the sensitivities of coordinates (x_{2},y_{2}) to a small node perturbation p_{i }along the normal {circumflex over (n)} are given by
As those skilled in the art can appreciate, the approach suggested above for defining a perturbation is in fact general and can be used to model any geometric perturbation of either the domain boundaries or the contact locations. All that is required is to determine the set of nodes defining the perturbation, determine the changes in the coordinates of these nodes in response to a unit variation, and finally determine the partial derivatives.
Complexity Analysis of Sensitivity Extraction
A FEM system matrix M is symmetric and very sparse. Moreover, by proper numbering of the nodes in the FEM mesh one can generate a banded system matrix M. The maximum bandwidth B of the matrix is the maximum difference between the global indices of any interacting noncontact nodes (e.g., nodes that share a common triangle). As discussed below, B is assumed a constant much smaller than N but in the order of both n_{p }and n_{o}. The most important observation is that the adjoint system matrix in formula (23) is the transpose of the matrix M. Because the matrix M is symmetric, both the linear system and the adjoint system have the same system matrix. Following all the previous observations the complete set of equations may be summarized as
The complexity of solving the first equation is that of solving the same nominal sparse linear system with multiple right hand sides. The number of right hand sides is equal to 1+n_{0}. Therefore, the complexity of solving all systems concurrently using Gaussian elimination is O(B^{2}N). In other words, the complexity of our method is independent of the number of outputs, and indeed, one of the main pitfalls of the adjoint sensitivity method is avoided. Namely, the linear growth of the complexity as a function of the number of outputs. The Gaussian elimination complexity is inherited from the solution of the nominal system and therefore the incremental complexity of solving both systems as compared to solving only the original system is insignificant. The added complexity of forming
which is n_{0 }matrixvector products, is O(n_{o}n_{p}) due to the sparsity of matrices C_{1 }and C_{2}. Finally, the complexity of forming the term
which is n_{p }sparse matrixvector products, is O(Nn_{p}). The total complexity is O(B^{2}N+n_{o}n_{p}+Nn_{p}), which is O(B^{2}N), i.e., it is the exact same complexity as solving only the nominal system. The memory complexity may also be shown to be O(B^{2}N), which is the same memory complexity as the one required to solve for nominal resistance alone.
Northbridge 915 and Southbridge 935 connect to each other using bus 919. In one embodiment, the bus is a Direct Media Interface (DMI) bus that transfers data at high speeds in each direction between Northbridge 915 and Southbridge 935. In another embodiment, a Peripheral Component Interconnect (PCI) bus connects the Northbridge and the Southbridge. Southbridge 935, also known as the I/O Controller Hub (ICH) is a chip that generally implements capabilities that operate at slower speeds than the capabilities provided by the Northbridge. Southbridge 935 typically provides various busses used to connect various components. These busses include, for example, PCI and PCI Express busses, an ISA bus, a System Management Bus (SMBus or SMB), and/or a Low Pin Count (LPC) bus. The LPC bus often connects lowbandwidth devices, such as boot ROM 996 and “legacy” I/O devices (using a “super I/O” chip). The “legacy” I/O devices (998) can include, for example, serial and parallel ports, keyboard, mouse, and/or a floppy disk controller. The LPC bus also connects Southbridge 935 to Trusted Platform Module (TPM) 995. Other components often included in Southbridge 935 include a Direct Memory Access (DMA) controller, a Programmable Interrupt Controller (PIC), and a storage device controller, which connects Southbridge 935 to nonvolatile storage device 985, such as a hard disk drive, using bus 984.
ExpressCard 955 is a slot that connects hotpluggable devices to the information handling system. ExpressCard 955 supports both PCI Express and USB connectivity as it connects to Southbridge 935 using both the Universal Serial Bus (USB) the PCI Express bus. Southbridge 935 includes USB Controller 940 that provides USB connectivity to devices that connect to the USB. These devices include webcam (camera) 950, infrared (IR) receiver 948, keyboard and trackpad 944, and Bluetooth device 946, which provides for wireless personal area networks (PANs). USB Controller 940 also provides USB connectivity to other miscellaneous USB connected devices 942, such as a mouse, removable nonvolatile storage device 945, modems, network cards, ISDN connectors, fax, printers, USB hubs, and many other types of USB connected devices. While removable nonvolatile storage device 945 is shown as a USBconnected device, removable nonvolatile storage device 945 could be connected using a different interface, such as a Firewire interface, etcetera.
Wireless Local Area Network (LAN) device 975 connects to Southbridge 935 via the PCI or PCI Express bus 972. LAN device 975 typically implements one of the IEEE 802.11 standards of overtheair modulation techniques that all use the same protocol to wirelessly communicate between information handling system 900 and another computer system or device. Optical storage device 990 connects to Southbridge 935 using Serial ATA (SATA) bus 988. Serial ATA adapters and devices communicate over a highspeed serial link. The Serial ATA bus also connects Southbridge 935 to other forms of storage devices, such as hard disk drives. Audio circuitry 960, such as a sound card, connects to Southbridge 935 via bus 958. Audio circuitry 960 also provides functionality such as audio linein and optical digital audio in port 962, optical digital output and headphone jack 964, internal speakers 966, and internal microphone 968. Ethernet controller 970 connects to Southbridge 935 using a bus, such as the PCI or PCI Express bus. Ethernet controller 970 connects information handling system 900 to a computer network, such as a Local Area Network (LAN), the Internet, and other public and private computer networks.
While
The Trusted Platform Module (TPM 995) shown in
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardwarebased systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
While particular embodiments of the present disclosure have been shown and described, it will be obvious to those skilled in the art that, based upon the teachings herein, that changes and modifications may be made without departing from this disclosure and its broader aspects. Therefore, the appended claims are to encompass within their scope all such changes and modifications as are within the true spirit and scope of this disclosure. Furthermore, it is to be understood that the disclosure is solely defined by the appended claims. It will be understood by those with skill in the art that if a specific number of an introduced claim element is intended, such intent will be explicitly recited in the claim, and in the absence of such recitation no such limitation is present. For nonlimiting example, as an aid to understanding, the following appended claims contain usage of the introductory phrases “at least one” and “one or more” to introduce claim elements. However, the use of such phrases should not be construed to imply that the introduction of a claim element by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim element to disclosures containing only one such element, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an”; the same holds true for the use in the claims of definite articles.
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